AI Engineering & Applied Machine Learning Master Program:
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Build Real AI Systems — from classical ML to production-ready LLMs — with hands-on projects in PyTorch, TensorFlow, LangChain, and open-source models
Bangalore
February 2026
Beginner to Job-Ready in 6 Months
Ideal for: Engineering grads, data science aspirants, software developers, and professionals aiming for AI/ML, LLM, or MLOps roles in product-driven companies.
Schedule
Balance learning and work with flexible weekday and weekend batch options
Duration
6-Month Path to Job Readiness - 3 months of hands-on training + 3 months of real-world internship.
Course Value
Capstone Project
Build a private RAG agent that answers questions from your documents — with citations, vector search, and a clean UI.
Assessments
Regular hands-on coding tasks, project submissions, and expert-reviewed evaluations to ensure true mastery.
Mentorship
Guided support session for real-time clarification and feedback
Workshop
Group sessions with industry experts on trends, career paths, & real-world insights.
LMS Access
Access to recorded sessions, learning materials, practice templates, and knowledgeable guides
Certification
Receive an industry-recognized certificate upon successful completion—validated by real project work.
Expertise you‘ll build
Classical ML: Regression, classification, SMOTE – applied to fraud detection & real-world stats problems
Deep Learning: ANNs, CNNs, RNNs/LSTMs in PyTorch/TensorFlow – for churn, imaging & more
Computer Vision: Transfer learning (ResNet/VGG) for X-rays, products, defect detection
Unsupervised Learning: Clustering, PCA/t-SNE – uncover user & behavioral patterns
NLP & Transformers: Fine-tune BERT for sentiment & toxicity using Hugging Face
Generative AI: Prompt engineering, Chain-of-Thought, and AI agents with LangChain
RAG Systems: Build PDF-to-chat apps with OpenAI, Sentence Transformers & Chroma/Pinecone
LLM Fine-Tuning: Adapt Llama-3/Mistral using LoRA/QLoRA – even on free Colab GPUs
Why choose this training program?
We teach you to build, deploy, and debug real AI systems, not just use ChatGPT. Become an AI engineer who ships, not just experiments.
Career Prospects
Land roles like Generative AI Engineer or LLM Developer at top firms that need engineers who ship production LLM apps.
Stand Out
Ship a Dockerized RAG app. Master LangChain internals, not just prompts. Optimize for cost, latency, and reliability.
Grow Further
Prep for cloud GenAI certs, contribute to open-source LLMs, and specialize in Agentic AI or AI Safety.
Future-Ready Skills
Master the full GenAI stack—from vector databases to deployment—keeping you ahead as the industry evolves.
Benefits of Choosing Us
Built for coders — no “no-code AI” here; you’ll write real Python every week
A comprehensive program that seamlessly integrates classical ML → deep learning → LLMs → RAG → fine-tuning in a single, industry-aligned learning flow.
Robust evaluation — tracked via code quality, project completeness, and deployment success
Dedicated program manager — your single point of contact for all logistical queries.
Career counseling — learn how to crack AI roles from engineers at product companies
Taught by builders — instructors who deploy AI / GenAI in production for large scale, not just run demos
Know your trainer
Rathan is a leading AI architect behind India’s most impactful digital public infrastructure. As Lead Architect of Bhashini (India’s national AI language program), he co-won the Economic Times CIO Award. He also built Anuvaad, the Supreme Court’s AI translation platform, commended by the President of India
His work spans the PM’s Dashboard, CPGRAMS (India’s largest grievance system), and agentic AI solutions for e-commerce and enterprise clients.
Holding a Ph.D. in AI (5 papers, 1 patent), he has trained teams at TCS and Hanover Insurance, uniquely bridging research, nation-scale deployment, and professional education.
Onboarding procedure
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